B cell profiles, antibody repertoire and reactivity reveal dysregulated responses with autoimmune features in melanoma

B cells are known to contribute to the anti-tumor immune response, especially in immunogenic tumors such as melanoma, yet humoral immunity has not been characterized in these cancers to detail. Here we show comprehensive phenotyping in samples of circulating and tumor-resident B cells as well as serum antibodies in melanoma patients. Memory B cells are enriched in tumors compared to blood in paired samples and feature distinct antibody repertoires, linked to specific isotypes. Tumor-associated B cells undergo clonal expansion, class switch recombination, somatic hypermutation and receptor revision. Compared with blood, tumor-associated B cells produce antibodies with proportionally higher levels of unproductive sequences and distinct complementarity determining region 3 properties. The observed features are signs of affinity maturation and polyreactivity and suggest an active and aberrant autoimmune-like reaction in the tumor microenvironment. Consistent with this, tumor-derived antibodies are polyreactive and characterized by autoantigen recognition. Serum antibodies show reactivity to antigens attributed to autoimmune diseases and cancer, and their levels are higher in patients with active disease compared to post-resection state. Our findings thus reveal B cell lineage dysregulation with distinct antibody repertoire and specificity, alongside clonally-expanded tumor-infiltrating B cells with autoimmune-like features, shaping the humoral immune response in melanoma.

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Software and code
Policy information about availability of computer code Data collection Mass cytometry data were acquired using CyTOF® Software v7.0.8493 for Fluidigm Helios. Flow cytometry data were acquired using BD FACSDiva v6.0 software. The publicly available dataset GSE123139 was acquired using R (RStudio, Version 1.3.1093). RSEM expected count (DESeq2 standardized) dataset from TCGA TARGET GTEx study (UCSC Xena) were obtained using Xena Browser (https://xenabrowser.net). Immunoglobulin long read sequences were acquired using PacBio Sequel 2 technology. Immuno mass spectrometry row data were generated using XCalibur software v.2.0.6 (Thermo Fisher Scientific). Immunofluorescence images were acquired with NIS-Elements software (Nikon).
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March 2021
Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A description of any restrictions on data availability -For clinical datasets or third party data, please ensure that the statement adheres to our policy The data generated in this study are provided in the Supplementary Information/Source Data file. The computer code generated in this study has been deposited in the following github repository: https://github.com/josef0731/melanoma-ig.

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Reporting on sex and gender Information on patients' and healthy volunteers' sex was collected based on self-reporting. Patients group has been designed to be sex-homogeneous and sex-based analyses were not included in this study.

Population characteristics
We selected metastatic melanoma patients (stage III and IV) who had not received immunotherapy treatment. Patients were male and female over the age of 18 years. We selected healthy volunteers with no history of malignancy to match patients' age.

Recruitment
This study focus on immunotherapy treatment naive patients (male and female) with metastatic melanoma (stages III -IV) over the age of 18 years and able to provide informed written consent were included and healthy volunteers (male and female) over the age of 18 years with no history of malignancy and able to provide informed written consent were included. Note that full information on the approval of the study protocol must also be provided in the manuscript.

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For CyTOF, flow cytometry and immuno-mass spectrometry analyses we have chosen a sample size of at least 25 patients (35, 29 and 33 patients, respectively), and we selected 13 age matched healthy volunteers for CyTOF analyses. Due to the variability of the parameters object of our study in tumor patients we chose to recruit a higher number of patients compared to healthy volunteers. The tumor samples analyzed by flow cytometry were 17, while, for tissue size availability and complexity of the experiment reasons, for spatial transcriptomics and Ig repertoire analyses we chose a sample size of 5 patients.
Data exclusions To characterize the B cell phenotypes in blood and tumor samples, of the 17 tumor samples analyzed by flow cytometry, 7 samples were excluded from the analysis because of the lack of B cells in the tumor (less than 10 B cells detected).

Replication
In this study we characterize B cell phenotypes, antibody repertoire and serum antibodies reactivity in melanoma patients. Each sample was considered biologically independent. Furthermore, when the samples have been analyzed in batches, we confirmed there were no batch effects.
Randomization Experimental groups were determined based on demographic information: we compared melanoma patients versus healthy volunteers, or melanoma patients' blood versus tumor, or samples from healthy volunteers versus stage III and stage IV patients.
The aim of this study is to characterize melanoma patients' B cell phenotypes, antibody repertoire and serum antibodies reactivity in immunotherapy naive patients, without the aim of correlating it to treatment outcome, for these reasons blinding was not relevant to this study.

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Cell line source(s) Expi293F™ Cells are human cells derived from the 293F cell line (GIBCO brand cells).

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Methodology Sample preparation
Peripheral blood mononuclear cells (PBMCs) were isolated from 40 ml blood (or leukocyte cones) using Ficoll® Paque Plus density centrifugation (GE Healthcare). Melanoma and skin tissue were minced with a scalpel and then mechanically dissociated with gentleMACS dissociator in RPMI 1640 medium supplemented with 1 mM EDTA. The cell suspension and the remaining pieces of tissue were then incubated overnight at 37°C, 5% CO2 in RPMI 1640 medium supplemented with 10% heat inactivated Fetal Bovine Serum (FBS) and Penicillin-Streptomycin (10,000 U/ml) to allow the remaining immune cells to crawl out of the tissue. The cell suspension was then harvested, passed through a 100 μm cell strainer, and processed for B cell phenotyping. PBMC and tumor single cell suspensions were stained with LIVE/DEAD Fixable Aqua ( Software BD FACSDiva™ Software was used to acquire the data, FlowJo (v10) was used to analyze the data, and GraphPad Prism (v9) was used for statistical analysis.

Cell population abundance
We analysed B cells from Peripheral blood mononuclear cells (PBMCs), in blood B cells are around 10% of CD45+ cells. We single cell sorted IgD-CD27+ B cells directly into lysis buffer for RNA extraction and cDNA preparation so we could not check the purity after sorting.
Gating strategy FSC and SSC parameters were used to exclude cell doublets and LIVE/DEAD Fixable Aqua was used to exclude dead cells. B cells were defined as CD45+ CD19+ cells. CD27 and IgD were used to define and characterize naive (CD27-IgD+) and memory (CD27+) B cells.
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